Crime and divorce. Can one lead to the other? Using Multilevel Mixed Models


Cross-sectional and time-series studies of the influence of divorce on crime and the reverse are few in developing and developed countries. Questions arise as to whether divorce causes crime, the reverse, or both effects exist in Jordan.

The objectives are to investigate the relationship between divorce and crime, determining whether the clustering in divorce and in crime within governorates exist and whether divorce and crime increase or decrease over time.

The study design was a cross-sectional time-series analysis. Several Jordanian statistical yearbooks and surveys issued by the Jordanian Statistics Department provided the data of 12 governorates over 14 years (2000–2013). After calculating the divorce rate (DR) and crime rate (CR), multilevel mixed-effects linear regression was performed, estimating three models each for divorce and crime. Comparison between these models was explained in intraclass correlation, the proportional change in the variance of the response variable, and the deviation.

The statistical and social epidemiological concepts of contextual phenomena confirm that the rates of divorce and crime in the same governorate are more similar to each other than to those from different governorates. Using the CR as a predictor for the DR reduced the within-governorate variance more than four times the between-governorates variance. Using the DR as a predictor for the CR reduced the within-governorate variance and inflated the between-governorates variance. Using time as a predictor for the DR reduced the within-governorate variance dramatically higher than the between-governorates variance and as a predictor for the CR reduced the within-governorate variance but inflated the between-governorates variance a small amount. Thus, both divorce and crime lead to the other.

Keywords: multilevel modeling; divorce; crime; time; governorate; intraclass correlation


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